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Editorial Team
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Editorial Team
Asked: May 13, 20262026-05-13T02:11:25+00:00 2026-05-13T02:11:25+00:00

I have a large table and I’d like to store the results in Memcache.

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I have a large table and I’d like to store the results in Memcache. I have Memcache set up on my server but there doesn’t seem to be any useful documentation (that I can find) on how to efficiently transfer large amounts of data. The only way that I currently can think of is to write a mysql query that grabs the key and value of the table and then saves that in Memcache. Its not a particularly scalable solution (especially when my query generates a few hundred thousand rows). Any advice on how to do this?

EDIT: there is some confusion about what I”m attempting to do. Lets say that I have a table with two fields (key and value). I am pulling in information on the fly and have to match it to the key and return the value. I’d like to avoid having to execute ~1000 queries per page load. Memcache seems like a perfect alternative because its set up to use key value. Lets say this table has 100K rows. THe only way that I know to get that data from the db table to memcache is to run a query that loops through every row in the table and creates an individual memcache row.

Questions: Is this a good way to use memcache? If yes, is there a better way to transfer my table?

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  1. Editorial Team
    Editorial Team
    2026-05-13T02:11:25+00:00Added an answer on May 13, 2026 at 2:11 am

    Russ,

    It sounds almost as if using a MySQL table with the storage engine set to MEMORY might be your way to go.

    A RAM based table gives you the flexibility of using SQL, and also prevents disk thrashing due to a large amount of reads/writes (like memcached).

    However, a RAM based table is very volatile. If anything is stored in the table and not flushed to a disk based table, and you lose power… well, you just lost your data. That being said, ensure you flush to a real disk-based table every once in a while.

    Also, another plus from using memory tables is you can store all the typical MySQL data types, so there is no 1MB size limit.

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